2016 INFORMS Annual Meeting Program

TA75

INFORMS Nashville – 2016

TA75 Legends C- Omni Behavioral Operations I Contributed Session Chair: Nazaré Rego, Escola de Economia e Gestão, Universidade do Minho, Braga, Portugal, nazare@eeg.uminho.pt 1 - Study Of Patient Satisfaction Perception Based On Medical Experience And Health Cognition Jianjie Zhang, Beijing Institute of Technology, Beijing, China, zhjj_2013@163.com, Jinlin LI, Rong Zhang, Jian Xue This paper examines patient experience and health cognition in outpatient from nine cities of China.By conducting discrete choice experiments,we identify discrepant patients in several attributes and the individual-difference about the health cognition that can explain such discrepancy.For the high degree of the health cognition patients,medical environment and waiting time affection is not significant.however,for the low degree of group,both two attributes affect significantly.In addition to providing the empirical description in China’s healthcare market,our study offers patient behavioral optimization suggestions to improve patient satisfaction perception. 2 - Detecting Market Irrationality Using News Sentiment Transfer Entropy Studies in behavioral finance have shown that investors are not rational, and market sentiment and returns have complex interactions. In this study we explore the non-linear relationship between news sentiment and market returns according to the transfer entropy statistic which identifies the amount of directional information flow. We identify two market regimes: sentiment dominance and market dominance. Further analysis suggests that the sentiment dominance indicates more irrational market activities contributing to elevated mispricing and high volatility, while market dominance reflects informational market efficiency. 3 - The Dark Side Of The Singularity: Can OR/MS Help? John D C Little, Institute Professor, Massachusetts Institute of Technology, M.I.T. Sloan School Of Management, Room E62-534, Cambridge, MA, 02142, United States, jlittle@mit.edu The “Singularity” is the point in time when artificial intelligence (AI) exceeds human intelligence. This may occur by putting AI on computers, by biological creation, or by a mixture of both. Some of the people writing about this or developing advanced AI are Victor Vinge, Ray Kurzweil (the Singularity is Near), Tom Malone, Ben Goertzel and Hugo de Garis. The dark side is that most people in this room will be left far behind. Kurzweil notes that AI develops exponentially, whereas most of us extrapolate linearly. 4 - Performance Effects Of Diversity Of Experience In Fluid Teams Antti Tenhiala, IE Business School, Madrid, Spain, antti.tenhiala@ie.edu, Constantin Alba, Fabrizio Salvador Analyzing fluid teams in a software services setting, we study the performance effects of diversity of experience, partitioning the diversity construct into three dimensions: segmentation, disparity, and variety. We also explore how project complexity moderates the performance effect of each diversity dimension. The results show that depending on the dimension, diversity of experience may have either negative, positive, or inverted-U relationship with team performance and that project complexity may make the effect either more beneficial or more detrimental. 5 - A System Dynamics Analysis Of Cautious Materials Management In Hospitals Nazaré Rego, Escola de Economia e Gestão, Universidade do Minho, Braga, Portugal, nazare@eeg.uminho.pt Nazaré Rego, INESC TEC, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal, nazare@eeg.uminho.pt, João Claro, Jorge Pinho de Sousa The supply system of a hospital provides a wide variety of services and products through a network composed of central departments and relatively autonomous wards. This system has to assure a high service level, particularly at critical wards. In this context, a just-in-case approach to inventory control has been frequently observed and, when the inventory at the DC is insufficient to meet all requests, priority in its allocation may be given to critical wards. We use System Dynamics to analyze the effect of these practices on inventory levels and related service level of a hospital supply system. Our results indicate that they may have a negative impact on the desired materials management outcomes. Anqi Liu, PhD Candidate, Stevens Institute of Technology, Hoboken, NJ, 07030, United States, aliu@stevens.edu, Steve Y Yang

2 - Disruption Management For Outbound Baggage Handling With Worker Assignment Christian Ruf, TU Muenchen, Arcisstr. 33, Munich, 80333, Germany, christian.ruf@tum.de Outbound baggage is transferred to departing airplanes. Flights have to be assigned to handling facilities, the handling has to be scheduled and workers have to be staffed to the flights. We propose a model and a solution procedure to plan the outbound baggage handling rolling planning fashion which allows for considering disruptions and updates of problem parameters at each decision epoch. In a computational study we show that the procedure is capable of giving a good solution in a reasonable amount of time even under severe disruptions. 3 - Demand Learning And Agreement Delay In Technology Adoption Wei Zhang, University of Hong Kong, Pokfulam Road, Hong Kong, China, zhangw.03@gmail.com Delay of price agreement is common when new technologies are being adopted. Existing theories attribute agreement delay in bilateral negotiations to either asymmetric information or behavioral constraints. We discover that incentives to learn about the uncertain demand drive delay of agreements, even when information is symmetric. Contrary to most existing theories, costly delay can benefit both negotiators. Chair: Abdulaziz Saud Alkabaa, Ph.D. Candidate, University of Tennesee, 1001 Cain Oak Place, Apt 1001, Knoxville, TN, 37909, United States, aalkabaa@vols.utk.edu 1 - Constraint Programming Models For The Irregular Cutting And Packing Problems Luiz Henrique Cherri, University of São Paulo, São Carlos, 13566-590, Brazil, luizcherri@gmail.com, Maria Antonia Carravilla, Cristina Ribeiro, Franklina M Toledo We propose new constraint programming models for variants of the two- dimensional irregular cutting and packing problem. In the literature, several heuristics were proposed for some problem variants, however there is no exact method or mathematical model for many of them. Using the constraint programming models we can represent and solve the irregular cutting and packing variants by exact methods. Since the enforcement of the no overlap among the pieces are the core constraints of all the problem variants, the formulations are built around this basis. 2 - An Iterative Method For Biobjective Mixed Integer Linear Programming Models Hadi Farhangi, Research Assistant, Missouri University of Science and Technology, 1870 Miner Circle, 236, Engineering Mgmt & Systems Eng, Rolla, MO, 65409, United States, hfrhc@mst.edu, Dincer Konur In this study, we propose an iterative method to generate the complete set of Pareto efficient solutions for biobjective mixed integer linear programming models. The Pareto efficient set is obtained by sequentially solving mixed integer linear programming models and utilizing the properties of the feasible search space. A numerical study demonstrates the performance of the solution method. 3 - Ensuring Scalability And Re-Usability Of Spreadsheet Analytical And Optimization Models Larry J LeBlanc, Professor, Vanderbilt University, Owen Graduate School of Mgmt, 401 21st Ave South, Nashville, TN, 37203, United States, larry.leblanc@owen.vanderbilt.edu, Thomas A Grossman Spreadsheet optimization models are harder than their algebraic counterparts to scale up and down in size. We show how to overcome this spreadsheet scalability disadvantage—We show how to program an optimization model in a spreadsheet that can easily be scaled up or down in size and re-optimized using the Excel Solver as easily as algebraic models. We give examples involving supply chain optimization. 4 - A Novel Branching Rule For Branch And Bound Based on Mahalanobis Distance Abdulaziz Saud Alkabaa, PhD Candidate, University of Tennesee, The critical rules affecting the Branch-and-Bound (B&B) algorithm’s solution performances are mostly regarded to the selection strategies of the search trees’ variables and nodes. These strategies can significantly impact on the algorithms’ efficiency. The available branching strategies in the literature, however, are not reliable in large problems (Linear Integer problems). In this research, we propose a novel branching strategy that is based on the concept of Mahalanobis Distance. Our analytical and numerical results show that the purposed strategy can effectively improve the B&B solution performances and works capably in a range of problem sizes. 1001 Cain Oak Place, Apt 1001, Knoxville, TN, 37909, United States, aalkabaa@vols.utk.edu, Alberto Garcia-Diaz TA74 Legends B- Omni Optimization Methodology I Contributed Session

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